Nankai University International E-Forum on Artificial Intelligence and Robotics

（第78期）

2026年南开大学人工智能与机器人国际学术讲坛

College of Artificial Intelligence, Nankai University

报告时间：2026年3月28日（周六）10:30~12:00

报告地点：南开大学津南校区人工智能学院北楼102会议室

报告嘉宾：Zhiqiang Zhang

专家单位：University of Leeds

报告题目：Understand Movement: How the Brain, Body, and Robots Can Work

报告摘要：

This talk explores how computational biomechanics, gait simulation, brain–computer interfaces, and human–robot interaction come together to advance movement science and rehabilitation. Using computational models of the neuromusculoskeletal system, we analyse how the brain and body produce movement by estimating internal movement variables (i.e., muscle forces and joint moments) which cannot be readily measured in vivo. These models then drive gait simulations, allowing realistic prediction of walking patterns while reducing experimental burden. Building on this foundation, brain–computer interfaces provide access to neural intent, linking brain signals with biomechanical and robotic models to better interpret voluntary movement or assist individuals with impaired motor control. Finally, these insights enable more natural human–robot interaction, where rehabilitation robots adapt to human movement and intention to provide safer, more personalised support, improving mobility and rehabilitation outcomes.

报告人简介：

Zhi-Qiang Zhang is Professor of Biomedical Engineering in the School of Electronics and Electrical Engineering. After getting his BEng in Computer Science from Tianjin University in 2005 and PhD in Electrical Engineering from the University of Chinese Academy of Sciences in 2010, he joined the Hamlyn Centre at Imperial College London as a postdoctoral researcher, and stayed there for five and half years. He joined the University of Leeds in 2016 as a University Academic Fellow and was promoted to Associate Professor in 2021, before becoming a Professor in 2024. His research combines computational biomechanics, computational modelling and simulation, brain-computer interfaces, and human-robot interaction to study how the brain and body produce movement and to develop intelligent rehabilitation robots that support mobility and recovery.